---
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C018_random_sample_llama3-8b-base_pretrain_20240504_182259
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# C018_random_sample_llama3-8b-base_pretrain_20240504_182259

This model is a fine-tuned version of [/data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base](https://huggingface.co//data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base) on the C018_random_sample_data dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2706

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1.5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 20
- num_epochs: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.3701        | 0.2186 | 200  | 2.3702          |
| 2.3183        | 0.4372 | 400  | 2.3160          |
| 2.2634        | 0.6557 | 600  | 2.2863          |
| 2.2522        | 0.8743 | 800  | 2.2706          |
| 2.0306        | 1.0929 | 1000 | 2.2777          |
| 2.0095        | 1.3115 | 1200 | 2.2760          |
| 2.0539        | 1.5301 | 1400 | 2.2746          |
| 2.0338        | 1.7486 | 1600 | 2.2743          |
| 2.0648        | 1.9672 | 1800 | 2.2737          |
| 2.0297        | 2.1858 | 2000 | 2.2766          |
| 2.0487        | 2.4044 | 2200 | 2.2767          |
| 2.0329        | 2.6230 | 2400 | 2.2770          |
| 2.0213        | 2.8415 | 2600 | 2.2766          |
| 2.0559        | 3.0601 | 2800 | 2.2771          |
| 2.0543        | 3.2787 | 3000 | 2.2773          |
| 2.0317        | 3.4973 | 3200 | 2.2772          |
| 1.988         | 3.7158 | 3400 | 2.2770          |
| 2.0355        | 3.9344 | 3600 | 2.2772          |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1